What problem does it solve? Designing competitive programming problems often lacks pedagogical rigor: vague learning objectives, miscalibrated difficulty, and constraints that fail to force the intended time complexity. This Skill produces a precise, machine-readable problem blueprint before any statement is written. ## Core Features & Use Cases - Structured Blueprint Generation: Outputs a validated architect_spec.json containing learning objective, prerequisites, difficulty rating, Bloom's level, tags, and constraint hints. - Difficulty & Constraint Calibration: Maps Codeforces rating tiers, DSA progression levels, and Bloom's taxonomy to concrete constraints using a constraint-to-complexity table. - Set Mode: Designs cohesive multi-problem sets with distribution ratios (comfortable/challenging/stretch), topic diversity rules, and difficulty ramping. - Use Case: Given the input "binary search on answer, rating 1400", produce a complete spec with a testable learning objective, 3-6 prerequisites, N bounds that force O(N log N), and a story direction ready for a problem-writing agent. ## Quick Start Ask the agent to design a competitive programming problem blueprint for a given topic, difficulty rating, and target audience, and receive a validated architect_spec.json.
